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Potential Customer Prediction
Author(s) -
Suyash S. Tambe,
Vivek Ambetkar,
Prathamesh Ambovkar
Publication year - 2021
Publication title -
international journal of engineering and management research
Language(s) - English
Resource type - Journals
eISSN - 2394-6962
pISSN - 2250-0758
DOI - 10.31033/ijemr.11.2.14
Subject(s) - computer science , profit (economics) , task (project management) , a priori and a posteriori , process (computing) , software , big data , data mining , operations research , engineering , systems engineering , philosophy , programming language , epistemology , economics , microeconomics , operating system
Major industries today are dealing with large amount of data even small shops are no oblivion for the huge pile of customer data. To gain profit in competitive marketing is imperative that the useful information shall be extracted out of this data. The processing of this huge pile of data becomes monotonous task and the different types of software and algorithms are developed to process and acquire result out of this data. This project deals with same kind of problem of dealing with data. Taking customer purchase history as an input our system using "Apriori Algoritm" classifies these customers as potential and non-potential customers. Customers who are potential are more likely to buy more from the store and help enhance business.

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